The Digital Signal Processing Lab @ UCSD


Thesis Title

Antenna Array Receiver Design and Analysis in Fast Fading Environments

Thesis Abstract

This thesis addresses the problem of data detection and channel estimation on multiple fast fading channels, i.e., multiple receive antennas. To characterize the temporal variation of fast fading process and evaluate its effect on the receiver structure and performance, we model the fast fading process as an autoregressive process. The optimal array receiver structure that minimizes the probability of error for BPSK signals is derived, which includes a Kalman filter to predict the fading channels. It also uses a variation of optimal combining to suppress interference. The error probability is analyzed and interesting special cases are studied to provide insight into the behavior of the derived receiver, which lower bounds the performance of practical receivers. We also apply the analysis to CDMA systems and obtain the performance result for matched filter receiver and minimum-output-energy receiver.

The above analysis is based on the assumption of perfect decision feedback. To reduce the effect of incorrect decision feedback, we propose soft decision feedback for adaptation. Particularly, an iterative receiver with soft decision feedback is systematically derived from the expectation-maximization algorithm, in the context of pilot symbol aided modulation. The optimization criterion is to achieve MAP estimation of the fading process. It is shown via simulation that soft decision feedback is better than hard decision feedback in a fast fading environment, with uncoded data, convolutional coded data and concatenated convolutional coded data.

Finally, as a starting point for research on multiple transmit antennas, we derive a closed form expression for the probability of error of maximal ratio transmission with two receive antennas and an arbitrary number of transmit antennas.

Year of Graduation: 2001